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Stability Indices to Deciphering the Genotype-by-Environment Interaction (GEI) Effect: An Applicable Review for Use

Alireza Pour-Aboughadareh1, Marouf Khalili2, Peter Poczai3

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Summary

Understanding genotype-by-environment interaction (GEI) is crucial for plant breeding. This review compiles GEI models and methods for stability analysis, aiding researchers in selecting superior genotypes.

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AMMI modelGGE biplotdynamic conceptgenotype-by-environment interaction (GEI)stability

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Area of Science:

  • Plant breeding
  • Quantitative genetics
  • Agricultural science

Background:

  • Genotype-by-environment interaction (GEI) is vital for optimizing crop performance in diverse conditions.
  • Traditional multi-environmental trials (METs) often mask GEI due to confounding factors like improved management.
  • Accurate GEI assessment is essential for effective plant breeding programs.

Purpose of the Study:

  • To review and consolidate various parametric and non-parametric models and methods for analyzing GEI.
  • To provide a comprehensive resource for researchers to understand and select appropriate stability analysis techniques.
  • To guide the selection of superior genotypes by dissecting the usefulness of different GEI assessment methods.

Main Methods:

  • Compilation of statistical methods and mathematical models for GEI analysis.
  • Categorization of methods into parametric and non-parametric approaches.
  • Alignment of each method with relevant software, macro codes, and/or scripts for practical application.

Main Results:

  • A comprehensive overview of GEI analysis techniques, including their underlying statistics and equations.
  • A structured approach to selecting appropriate methods based on specific research needs.
  • Identification of associated computational tools to facilitate the application of these methods.

Conclusions:

  • This review offers a valuable resource for plant breeders and researchers studying GEI.
  • The provided compilation and alignment of methods with software aim to enhance the accuracy and efficiency of genotype selection.
  • Understanding and applying diverse GEI analysis methods are key to advancing plant breeding and crop improvement.